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Prognostic Models for Predicting Overall Survival in Patients with Primary Gastric Cancer: A Systematic Review.
Feng, Qi; May, Margaret T; Ingle, Suzanne; Lu, Ming; Yang, Zuyao; Tang, Jinling.
Afiliação
  • Feng Q; Division of Epidemiology, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
  • May MT; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Ingle S; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Lu M; Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of GI Medical Oncology, Peking University Cancer Hospital & Institute, Beijing, China.
  • Yang Z; Division of Epidemiology, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
  • Tang J; Cochrane Hong Kong, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.
Biomed Res Int ; 2019: 5634598, 2019.
Article em En | MEDLINE | ID: mdl-31641669
ABSTRACT

BACKGROUND:

This study was designed to review the methodology and reporting of gastric cancer prognostic models and identify potential problems in model development.

METHODS:

This systematic review was conducted following the CHARMS checklist. MEDLINE and EMBASE were searched. Information on patient characteristics, methodological details, and models' performance was extracted. Descriptive statistics was used to summarize the methodological and reporting quality.

RESULTS:

In total, 101 model developments and 32 external validations were included. The median (range) of training sample size, number of death, and number of final predictors were 360 (29 to 15320), 193 (14 to 9560), and 5 (2 to 53), respectively. Ninety-one models were developed from routine clinical data. Statistical assumptions were reported to be checked in only nine models. Most model developments (94/101) used complete-case analysis. Discrimination and calibration were not reported in 33 and 55 models, respectively. The majority of models (81/101) have never been externally validated. None of the models have been evaluated regarding clinical impact.

CONCLUSIONS:

Many prognostic models have been developed, but their usefulness in clinical practice remains uncertain due to methodological shortcomings, insufficient reporting, and lack of external validation and impact studies. IMPACT Future research should improve methodological and reporting quality and emphasize more on external validation and impact assessment.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Biomed Res Int Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Gástricas Tipo de estudo: Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Humans Idioma: En Revista: Biomed Res Int Ano de publicação: 2019 Tipo de documento: Article País de afiliação: China
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